Dakota Reference Manual  Version 6.12
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Constrained Optimization BY Linear Approximations (COBYLA)


This keyword is related to the topics:


Alias: none

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional initial_delta

Reasonable initial changes to optimization variables

Optional variable_tolerance

Required or expected accuracy in optimization variables.

Optional solution_target Stopping criteria based on objective function value
Optional seed

Seed of the random number generator

Optional show_misc_options Show algorithm parameters not exposed in Dakota input
Optional misc_options Set method options not available through Dakota spec
Optional max_iterations

Number of iterations allowed for optimizers and adaptive UQ methods

Optional convergence_tolerance

Stopping criterion based on objective function or statistics convergence

Optional max_function_evaluations

Number of function evaluations allowed for optimizers

Optional scaling

Turn on scaling for variables, responses, and constraints

Optional model_pointer

Identifier for model block to be used by a method


The Constrained Optimization BY Linear Approximations (COBYLA) algorithm is an extension to the Nelder-Mead simplex algorithm for handling general linear/nonlinear constraints and is invoked using the coliny_cobyla group specification. The COBYLA algorithm employs linear approximations to the objective and constraint functions, the approximations being formed by linear interpolation at N+1 points in the space of the variables. We regard these interpolation points as vertices of a simplex. The step length parameter controls the size of the simplex and it is reduced automatically from initial_delta to variable_tolerance. One advantage that COBYLA has over many of its competitors is that it treats each constraint individually when calculating a change to the variables, instead of lumping the constraints together into a single penalty function.

See the page package_scolib for important information regarding all SCOLIB methods

coliny_cobyla is inherently serial.

Stopping Critieria

COBYLA currently only supports termination based on

Other method-independent stopping criteria (max_iterations and convergence_tolerance) will be ignored if set.

Known Bugs

The implementation of the coliny_cobyla optimization method is such that the best function value is not always returned to Dakota for reporting. The user is advised to look through the Dakota screen output or the tabular output file (if generated) to confirm what the best function value and corresponding parameter values are.

The coliny_cobyla optimization method does not always respect bound constraints when scaling is turned on.

Neither bug will be fixed, as maintaining third-party source code (such as COBYLA) is outside of the Dakota project scope.

Expected HDF5 Output

If Dakota was built with HDF5 support and run with the hdf5 keyword, this method writes the following results to HDF5:

See Also

These keywords may also be of interest: